BSC4024109 Project Details
| Supervisor | Zhao Dongsheng |
| Project Code | BSC4024109 |
| Title of Project | Formal concept analysis and applications |
| Description | Formal concept analysis (FCA) is a method of data analysis with growing popularity across various domains. FCA analyzes data which describe relationship between a particular set of objects and a particular set of attributes (properties). Such data commonly appear in many areas of human activities. A concept lattice is a collection of formal concepts in the data which are hierarchically ordered by a subconcept-superconcept relation. Formal concepts are particular clusters which represent natural human-like concepts such as “organism living in water”, “car with all wheel drive system”, “number divisible by 3 and 4”. The second output of FCA is a collection of so-called attribute implications. An attribute implication describes a particular dependency which is valid in the data such as “every number divisible by 3 and 4 is divisible by 6”, “every respondent with age over 60 is retired”. The mathematics foundation of FCA are the partially ordered sets and lattices. The applications of FCA have been found in many areas such as data mining, text mining, machine learning, knowledge management, semantic web, software development. In the project, the candidate will learn the theory of concept analysis and examine some concrete applications. |
| Pre-requisites | Nil |
| References | 1. R. Belohlavek, Introduction to Formal Concept Analysis. 2. Wolfgang Hesse, Formal Concept Analysis Used for Software Analysis and Modelling. 3. D. I. Ignatov, Introduction to Formal Concept Analysis and Its Applications in Information Retrieval and Related Fields. |